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Optimum Energy Production in Hydroelectric Power Plants

Yıl 2025, Cilt: 18 Sayı: 2, 594 - 617, 31.08.2025
https://doi.org/10.18185/erzifbed.1655660

Öz

In this study, it is aimed to obtain the highest energy that can be obtained from hydroelectric power plants (HPP) by providing minimum water consumption. Accordingly, with the Particle Swarm Optimization (PSO) method applied according to the characteristics of the plants specified in the study (Atatürk, Karakaya, Keban, Altınkaya and Deriner), the highest electricity production capacities that can be produced from the plants were obtained by reaching the optimum flow rate, water consumption value from the Matlab/Simulink model diagrams. The best solution obtained according to the PSO algorithm method is presented in terms of global best (Gbest), particle best (Pbest) energy production and water consumption. Energy production and target function values (fitness) for each flow rate range were tried to be determined pointwise. As a result, existing or new HEPP’s to be established should be provided with a balance between energy production and water consumption, sustainable, well-manageable and more efficient.

Kaynakça

  • [1] Yüksel, İ. (2008). Hydropower in Turkey for a clean and sustainable energy future. Renewable and Sustainable Energy Reviews. 12(6), 1622-1640.
  • [2] Sözen, A., Alp, İ., Kılınç, C. (2012). Efficiency assessment of the hydro-power plants in Turkey by using Data Envelopment Analysis. Renewable Energy, 46, 192-202.
  • [3] Bilgili, M. & All. (2018). The role of hydropower installations for sustainable energy development in Turkey and the world. Renewable Energy, 126, 755-764.
  • [4]Emeç, Ş., Adar, T., Akkaya, G., Delice, E.K. (2019). Efficiency Assessment of Hydroelectric Power Plant in Turkey by Data Envelopment Analysis (DEA). European Journal of Science and Technology, Special Issue, 34-45.
  • [5] Marcelinoa, C. G., Leite, G.M.C., Delgado, C.A.D.M., Oliveira, L.B., Wannerd, E.F., Jiménez-Fernándeza, S., & Salcedo-Sanz, S. (2021). An Efficient Multi-Objective Evolutionary Approach for Solving the Operation of Multi-Reservoir System Scheduling in Hydro-Power Plants. Preprint submitted to Expert Systems with Applications (ESWA 115638).
  • [6]Şavkar, E. (2024). Yenilenebilir enerji zemininde hidroelektrik enerji ve Türkiye potansiyeli. Oğuzhan Sosyal Bilimler Dergisi, 6(1), 51-58.
  • [7] Doğan, B., & Atak, N.N. (2024). Selection of Suitable Turbines and Power Calculations for Hydroelectric Power Plants (HPP) That Can Be Established in the Streams Located in The Black Sea Region. Alpha Journal of Engineering and Applied Sciences, 2(1), 17-32.
  • [8] Türkiye Elektrik İletim A.Ş. (TEİAŞ) Genel Müdürlüğü. (17 Şubat 2025). https://www.teias.gov.tr/
  • [9] http://cografyaharita.com/turkiye_enerji_haritalari.html (Erişim Tarihi 2025). Türkiye HES Kurulu Güç Yoğunluk Haritası.
  • [10] https://www.teias.gov.tr/aylik-elektrik-uretim-tuketim-raporlari (Erişim Tarihi 2024). TEİAŞ. Aylık Elektrik Üretim-Tüketim Raporları.
  • [11] https://www.enerjiatlasi.com/en-buyuk/hidroelektrik (Erişim Tarihi 2025). Türkiye’nin En Büyük 10 Hidroelektrik Enerji Santrali.
  • [12] Ervural, Ç. B., Ervural, B., Evren, R., (2016). Optimization Models in Energy: A Literature Review. Ege Academic Review. 16, 51-70.
  • https://tr.wikipedia.org/wiki/Deriner_Baraj%C4%B1_ve_Hidroelektrik_Santrali [14] Kennedy, J., 2024). Deriner Barajı ve Hidroelektrik Santrali. Vikipedi. & Eberhart, R., (1995). Particle swarm optimization. Proceedings of ICNN'95 - International Conference on Neural Networks.
  • [15] Kaewarsa, S., & Kongpaseuth, V., (2024). Hydropower Plant Available Energy Forecasting Using Artificial Neural Network and Particle Swarm Optimization. Electricity, 5(4), 751-769.
  • [16]Castro-Freibott, R., García-Castellano Gerbolés, C., García-Sánchez, A. et. al. (2024). MILP and PSO approaches for solving a hydropower reservoirs intraday economic optimization problem. Central European Journal of Operations Research.
  • [17] Çelikdemir, S., & Özdemir, M. T. (2023). Development of Small Hydroelectric Power Plant Maintenance Costs using Chaos Embedded Adaptive Particle Swarm Optimization. Journal of Advanced Research in Natural and Applied Sciences, 9(4), 788-803.
  • [18]Joshi, M., Sharma, G., & Çelik, E. (2023). Load Frequency Control of Hydro-Hydro Power System using Fuzzy-PSO-PID with Application of UC and RFB. Electric Power Components and Systems, 51(12), 1156–1170.
  • [19] Güven, A., Yörükeren, N., (2022). Energy Management and Optimization of a Hybrid Energy System by Particle Swarm Optimizing Algorithm-Genetic Algorithm and Gray Wolf Optimizing Algorithm Technique: A case study for Yalova University. Black Sea Journal of Science, 12(2), 853-879.
  • [20] Tiryaki, H., & Gün, A. (2019). Modern Optimizasyon Yöntemleri ile Bir Hidroelektrik Santralde Frekans Kontrolü. International Journal of Engineering Research and Development, 11(1), 266-274.
  • [21] Ekinci, S., Hekimoğlu B. (2017). Coordinated Design of TCSC and PSS by Using PSO Algorithm for Enhancement of SMIB Power System Stability. Batman University Journal of Life Sciences, 7(1/2), 9-21

Hidroelektrik Santrallerde Optimum Enerji Üretimi

Yıl 2025, Cilt: 18 Sayı: 2, 594 - 617, 31.08.2025
https://doi.org/10.18185/erzifbed.1655660

Öz

Yapılan bu çalışmada, hidroelektrik enerji santralinden (HES) elde edilebilecek en yüksek enerjiyi minimum su sarfiyatı sağlayarak elde edilebilmesi amaçlanmıştır. Buna göre çalışma içerisinde belirtilen santral (Atatürk, Karakaya, Keban, Altınkaya ve Deriner) özelliklerine göre uygulanan Parçacık Sürü Optimizasyon (Particul Swarm Optimization-PSO) yöntemiyle, Matlab/Simulink model diyagramlarından optimum debi yani su tüketimi değerine ulaşılarak santrallerden üretilebilecek en yüksek elektrik üretim kapasiteleri elde edilmiştir. PSO algoritma yöntemine göre elde edilen en iyi çözüm global en iyi (Gbest), parçacık en iyi (Pbest) enerji üretimi ve su tüketimi açısından optimize edilmiş değerler sunulmuştur. Her bir debi aralığı için enerji üretimi ve hedef fonksiyon değerleri (fitness) noktasal olarak belirlenmeye çalışılmıştır. Sonuçta var olan veya kurulacak olan yeni HES’lerin enerji üretimi ve su sarfiyatı arasında bir denge olacak şekilde, sürdürülebilir iyi yönetilebilirliği ve daha verimli olması sağlanmalıdır.

Kaynakça

  • [1] Yüksel, İ. (2008). Hydropower in Turkey for a clean and sustainable energy future. Renewable and Sustainable Energy Reviews. 12(6), 1622-1640.
  • [2] Sözen, A., Alp, İ., Kılınç, C. (2012). Efficiency assessment of the hydro-power plants in Turkey by using Data Envelopment Analysis. Renewable Energy, 46, 192-202.
  • [3] Bilgili, M. & All. (2018). The role of hydropower installations for sustainable energy development in Turkey and the world. Renewable Energy, 126, 755-764.
  • [4]Emeç, Ş., Adar, T., Akkaya, G., Delice, E.K. (2019). Efficiency Assessment of Hydroelectric Power Plant in Turkey by Data Envelopment Analysis (DEA). European Journal of Science and Technology, Special Issue, 34-45.
  • [5] Marcelinoa, C. G., Leite, G.M.C., Delgado, C.A.D.M., Oliveira, L.B., Wannerd, E.F., Jiménez-Fernándeza, S., & Salcedo-Sanz, S. (2021). An Efficient Multi-Objective Evolutionary Approach for Solving the Operation of Multi-Reservoir System Scheduling in Hydro-Power Plants. Preprint submitted to Expert Systems with Applications (ESWA 115638).
  • [6]Şavkar, E. (2024). Yenilenebilir enerji zemininde hidroelektrik enerji ve Türkiye potansiyeli. Oğuzhan Sosyal Bilimler Dergisi, 6(1), 51-58.
  • [7] Doğan, B., & Atak, N.N. (2024). Selection of Suitable Turbines and Power Calculations for Hydroelectric Power Plants (HPP) That Can Be Established in the Streams Located in The Black Sea Region. Alpha Journal of Engineering and Applied Sciences, 2(1), 17-32.
  • [8] Türkiye Elektrik İletim A.Ş. (TEİAŞ) Genel Müdürlüğü. (17 Şubat 2025). https://www.teias.gov.tr/
  • [9] http://cografyaharita.com/turkiye_enerji_haritalari.html (Erişim Tarihi 2025). Türkiye HES Kurulu Güç Yoğunluk Haritası.
  • [10] https://www.teias.gov.tr/aylik-elektrik-uretim-tuketim-raporlari (Erişim Tarihi 2024). TEİAŞ. Aylık Elektrik Üretim-Tüketim Raporları.
  • [11] https://www.enerjiatlasi.com/en-buyuk/hidroelektrik (Erişim Tarihi 2025). Türkiye’nin En Büyük 10 Hidroelektrik Enerji Santrali.
  • [12] Ervural, Ç. B., Ervural, B., Evren, R., (2016). Optimization Models in Energy: A Literature Review. Ege Academic Review. 16, 51-70.
  • https://tr.wikipedia.org/wiki/Deriner_Baraj%C4%B1_ve_Hidroelektrik_Santrali [14] Kennedy, J., 2024). Deriner Barajı ve Hidroelektrik Santrali. Vikipedi. & Eberhart, R., (1995). Particle swarm optimization. Proceedings of ICNN'95 - International Conference on Neural Networks.
  • [15] Kaewarsa, S., & Kongpaseuth, V., (2024). Hydropower Plant Available Energy Forecasting Using Artificial Neural Network and Particle Swarm Optimization. Electricity, 5(4), 751-769.
  • [16]Castro-Freibott, R., García-Castellano Gerbolés, C., García-Sánchez, A. et. al. (2024). MILP and PSO approaches for solving a hydropower reservoirs intraday economic optimization problem. Central European Journal of Operations Research.
  • [17] Çelikdemir, S., & Özdemir, M. T. (2023). Development of Small Hydroelectric Power Plant Maintenance Costs using Chaos Embedded Adaptive Particle Swarm Optimization. Journal of Advanced Research in Natural and Applied Sciences, 9(4), 788-803.
  • [18]Joshi, M., Sharma, G., & Çelik, E. (2023). Load Frequency Control of Hydro-Hydro Power System using Fuzzy-PSO-PID with Application of UC and RFB. Electric Power Components and Systems, 51(12), 1156–1170.
  • [19] Güven, A., Yörükeren, N., (2022). Energy Management and Optimization of a Hybrid Energy System by Particle Swarm Optimizing Algorithm-Genetic Algorithm and Gray Wolf Optimizing Algorithm Technique: A case study for Yalova University. Black Sea Journal of Science, 12(2), 853-879.
  • [20] Tiryaki, H., & Gün, A. (2019). Modern Optimizasyon Yöntemleri ile Bir Hidroelektrik Santralde Frekans Kontrolü. International Journal of Engineering Research and Development, 11(1), 266-274.
  • [21] Ekinci, S., Hekimoğlu B. (2017). Coordinated Design of TCSC and PSS by Using PSO Algorithm for Enhancement of SMIB Power System Stability. Batman University Journal of Life Sciences, 7(1/2), 9-21
Toplam 20 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Enerji Üretimi, Dönüşüm ve Depolama (Kimyasal ve Elektiksel hariç), Makine Mühendisliğinde Optimizasyon Teknikleri, Makine Mühendisliği (Diğer)
Bölüm Makaleler
Yazarlar

Ufuk Bilmiş 0000-0001-7855-9582

İsak Kotcioğlu 0000-0002-7309-4840

Erken Görünüm Tarihi 14 Ağustos 2025
Yayımlanma Tarihi 31 Ağustos 2025
Gönderilme Tarihi 11 Mart 2025
Kabul Tarihi 17 Nisan 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 18 Sayı: 2

Kaynak Göster

APA Bilmiş, U., & Kotcioğlu, İ. (2025). Optimum Energy Production in Hydroelectric Power Plants. Erzincan University Journal of Science and Technology, 18(2), 594-617. https://doi.org/10.18185/erzifbed.1655660